At Atila, we’re trying to provide all students with access to funding for a quality education. This is a big problem with many moving parts and the challenges can be very complex. This article will give you an idea of the software stack we use to solve this problem and some advice on how to choose a software stack for your company as well.
Broadly speaking, I generally spend most of my time thinking about two things, technology and investing. More specifically, I often ask myself what is something useful I can build with software (or occasionally hardware) and what is something useful which I should invest in. Algorithmic trading is a nice integration of these two schools and I have been spending some time understanding this field. This is an intriguing field and I learnt some interesting things which I decided to share.
For my summer internship, my project involves using machine learning to help small businesses with funding. I learned a lot about machine learning in the process, so I gave a talk about it to some of my co-workers and shared the slides online:
I also shared the code on my Github. The following is an essay version of the talk.
Before I say anything, I want to show you a video from the 2017 WWDC Apple conference, WWDC is the annual conference which Apple hosts and is one of the most important events in the tech calendar for showcasing the top technology applications that will be used in the near future.
Apple wants you to know that they're really focused on machine learning pic.twitter.com/ZCJvBPGQpi
— VICE News (@vicenews) June 6, 2017
So the machine learning supercut gives some context to how I think society generally views machine learning. On the one hand, it’s a technology which has a lot of potential and will drastically change aspects of our society. Conversely, because it has so much potential people have a tendency to over promise and over-advertise the things which machine learning is capable of doing and often turn it into a marketing gimmick and annoying buzzword. For a high level, non-technical summary of what machine learning is about and what the future of technology in general, I recommend Homo Sapiens by Yuval Noah Harari.
I take a more middle-ground approach and say that you should judge it on the merits of what you can actually build with machine learning, but first, you have to understand what machine learning is.
(Guage audience level) How many of you: has never coded before… used ML in a small side project … Studied ML at a Master’s or Ph.D. Level, written or helped write a paper about ML etc.)I’ve tried to structure my talk in such a way that non-technical people will find it interesting and the more technical, ML-experienced people may some new, interesting concepts.
The reason my talk is called practical machine learning is because I consider myself a very pragmatic, practical person and whenever I learn something, the first thing I ask myself is how can I apply what I’ve learned and put it into practice. Hopefully, after today’s talk, you will hopefully be able to apply what you’ve learned and build actual ML projects. Alright, so let’s get started
What is Machine Learning?
My talk was greatly inspired by 2 tutorials which I did, the website is awesome and the guy who runs it Harrison Kinley is a very good teacher.
- Also, speaks to a pattern of whenever people say “Computers will never be able to do X because they need a certain skill that only humans have”. It’s usually just a matter of time before computers acquire those skills.
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|1.||↑||I forget the exact number, but I’m just repeating what Scott Galloway said|
When I think about the next five, 25, 50 years I often ask myself, “What things will be better in the future? What things will be worse? And how do I best prepare?” I tend to oscillate between excitement-hopefulness and mild paranoia. I have now decided to split the difference between optimism and pessimism and say that I will be Optimistic but Hedged.
The world population is expected to reach 9.6 billion by mid-2050. Countries with lower standards of living typically have higher population growth rates. The Food and Agriculture Organization of the United Nations (FAO) estimates food production will need to double in some parts of the world by 2050. The confluence of these three factors raises the question of how are we going to feed these many people.
Nigeria’s petroleum industry is very peculiar. Despite producing 1.75 million barrels of crude oil per day(b/d), they only refine about 24,000 barrels into gasoline, leaving them 384,000 barrels short of meeting daily domestic demand.
This is a test post, the source can be found here.
The world we live in is not a fair place and we are not all born into this world through ideal circumstances. Despite Thomas Jefferson’s idealistic sentiment,[note] A test footnote for when I am inclined to diverge on a tangent[/note]
all men are not created equal and not all people are privy to equal opportunities.
This grim reality is illustrated in most places in the world, but especially true in third world countries.
The country whose interests are dearest to my heart is the Federal Republic of Nigeria. Nigeria is a classic example of a nation where the divisions between the upper and lower classes are exceptionally stark and the divisions are exacerbated by a dwindling middle class. I won’t discuss philosophically whether or not it is fair that certain people are born into greater privilege than others because that is simply an unfortunate but unavoidable fact of life. However, I am greatly concerned by the lottery we play in Nigeria concerning the education of our youth. This unequal access to education is the origin of what perpetuates classist divisions in Nigeria.
The primary cause of this statistical inequity is one which has plagued humans since the beginning of time, the human weakness of greed. Echoing, biblical history when Judas betrayed Jesus for thirty silver shekels, Nigerian politicians betray their own people for millions of dollars a year.
- There was a time when Nigerian schools delivered an effective education to the extent that there was little difference between sending your children to a local school and sending your children to a school abroad.
- There was also little distinction between a child who had been educated at a public school and one who had attended a private school because the public school system was quite strong.
- However, problems slowly began to arise after Nigeria gained independence from the British in 1967.